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Building a Language Data Set in Telugu Using Machine Learning Techniques to Address Suicidal Ideation and Behaviors in Adolescents Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Feature Selection and Performance Comparison of Various Machine Learning Classifiers for Analyzing Students’ Performance Using Rapid Miner

Authors : Vikas Rattan, Varun Malik, Ruchi Mittal, Jaiteg Singh, Pawan Kumar Chand

Published in: Applications of Artificial Intelligence and Machine Learning

Publisher: Springer Singapore

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Abstract

Information technology revolution and affordable cost of storage devices and Internet usage tariff have made it easy for educational bodies to collect data of every stake holder involved in. This collected data has many hidden facts, and, if extracted, it can give new insights to every concerned contributor. The educational bodies can use educational data mining to examine and predict the performance of students which helps them to take remedial action for weaker students. In education data mining, classification is the most popular technique. In this paper, emphasis is on predicting students’ performance using various machine learning classifiers and the comparative analysis of performance of learning classifiers on an educational dataset.

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Metadata
Title
Feature Selection and Performance Comparison of Various Machine Learning Classifiers for Analyzing Students’ Performance Using Rapid Miner
Authors
Vikas Rattan
Varun Malik
Ruchi Mittal
Jaiteg Singh
Pawan Kumar Chand
Copyright Year
2021
Publisher
Springer Singapore
Book
Applications of Artificial Intelligence and Machine Learning

Print ISBN: 978-981-16-3066-8

Electronic ISBN: 978-981-16-3067-5

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-16-3067-5_2

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